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def read_google_cvs(gss_url="http://spreadsheets.google.com",\
    gss_format="csv",\
    gss_key="0AuLa_xuSIEvxdERYSGVQWDBTX1NCN19QMXVpb0lhWXc",\
    gss_sheet=0,\
    gss_query="select B,D,E,F,I where (H contains 'GFIF') order by D desc",\
    gss_keep_default_na=False
    ):
    import urllib
    import pandas as pd
    """

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{
 "metadata": {
  "name": "",
  "signature": "sha256:94039565962d0f8184f6e8b9e9d2f1c0ba1e0b4c7a3e8fefc78226ac661d5f65"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [

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#!/usr/bin/env python
import os.path
import random
import time
def multiplicar(a,b):
   resultado=input('%sx%s = ' %(a,b))
   if resultado==a*b:
       return True
   else:
       print('Error! el resultado correcto es: %s' %(a*b))

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{
 "metadata": {
  "name": "t12aparallel",
  "signature": "sha256:592681c554e9742e6e0d910855060e314fd9070ccc64be9e0a6d2e7f4e314130"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [

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diff --git a/butler b/butler
index 08fbcf1..0f187c7 100755
--- a/butler
+++ b/butler
@@ -33,6 +33,7 @@ valid options are:
                         spheno , calchep , micromegas , whizard , 
                         madgraph , ssp
    --skip-sarah       : skip the SARAH run and use an existing result
+   --yes              : Assume that the answer to simple yes/no questions is 'yes'
 EOI

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